Spatio-temporal classification of land use and land cover and its changes in Kerala using remote sensing and machine learning approach

Vijay, Anjali; Varija, K.

doi:10.1007/s10661-024-12633-y

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2024

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Cited by 2 publications

References 84 publications

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Data mining techniques for LULC analysis using sparse labels and multisource data integration for the hilly terrain of Nilgiris district, Tamil Nadu, India

Kumaraperumal,

Raj,

Pazhanivelan

et al. 2024

Earth Sci Inform

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Data mining techniques for LULC analysis using sparse labels and multisource data integration for the hilly terrain of Nilgiris district, Tamil Nadu, India

Kumaraperumal,

Raj,

Pazhanivelan

et al. 2024

Earth Sci Inform

View full text Add to dashboard Cite

Geospatial delineation of groundwater potential zones in the lower Okavango Delta, Botswana

Gondo

2024

Preprint

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Integration of remote sensing and geographical information systems (GIS) is crucial in groundwater resource management, particularly in regions like the Okavango Delta in Northern Botswana, characterized by erratic rainfall ranging annually and spatially from 300 to 600 millimetres. This variability, coupled with occasional droughts, poses significant risks to water resources, agriculture, and livelihoods. To tackle these challenges, this study employed remote sensing and GIS techniques to delineate groundwater potential zones (GWPZs) in the lower Okavango Delta. The Analytical Hierarchy Process (AHP) was utilized to analyse eight thematic factors—geology, rainfall, slope, lineament density, soil, drainage density and land use, and land cover—and integrate them into the groundwater potential zone map. The study identified five distinct GWPZs: very poor (2.8%), poor (44.5%), moderate (45.0%), good (7.6%), and very good (0.1%), indicating varying degrees of groundwater availability and suitability for sustainable use. Integrating this potential zone map into broader water resource management plans is recommended to promote sustainable groundwater management practices. Additionally, enhancing climate resilience through cross-sectoral collaboration and stakeholder engagement is crucial. These efforts are necessary for developing integrated strategies to address water resource planning and adapt to climate change impacts, fostering sustainable development and resilience in water-stressed regions.

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Spatio-temporal classification of land use and land cover and its changes in Kerala using remote sensing and machine learning approach

Cited by 2 publications

References 84 publications

Data mining techniques for LULC analysis using sparse labels and multisource data integration for the hilly terrain of Nilgiris district, Tamil Nadu, India

Data mining techniques for LULC analysis using sparse labels and multisource data integration for the hilly terrain of Nilgiris district, Tamil Nadu, India

Geospatial delineation of groundwater potential zones in the lower Okavango Delta, Botswana

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